Hiring? Approving Mortgages? It’s the Same Thing (Risk …)

Traditionally hiring and approving mortgage are completely different problems. But, when you look at them from a data science perspective, both things do have similar characteristics.

By Greta Roberts, CEO Talent Analytics.

Imagine that Chris wants to buy a house and needs a mortgage. He applies online and is sent an email by an intern asking to schedule time to discuss his interest. The intern conducts the initial screening conversation, they schedule him for an in person interview during which time he is interviewed by quite a few folks who ask many questions.

Chris is curious because nobody asks about his current job or how he expects to pay the mortgage. Nobody asks about other credit or past credit history. They seem more interested in his current zip code, engagement in his current community and other demographics. They ask if it’s ok to review his social media data – which feels invasive and perhaps irrelevant, but he agrees because he really needs the mortgage.

Success! Mortgage is Approved

Chris is surprised when they approve him for the loan. He's done his own budgeting and it seems risky. But he really wants the house. Approving mortgages is their business, so he places some value in their risk assessment process. Don't they know the factors that signal / predict successful and unsuccessful creditors?

6 months later, Chris struggles to pay his mortgage and begins to fall behind on payments. He explains his situation to the mortgage manager. They are able to restructure the mortgage, giving him more years to pay it off and smaller payments.He works with their credit counselors and even agrees to attend training to learn more. He struggles and tries to make his mortgage payments through the next year. He means well but he just can't pay his bills. Finally, Chris files for bankruptcy.

He loses his home. The lender has a terrible financial loss but repeats the same exact process with the same person who wants a mortgage. Or maybe they'll change it up a little and ask some different questions.

Obviously, this isn't how lenders make decisions about extending mortgages. They'd go out of business. Lending money is a repeatable process that can be studied with data science. They decide there have to be factors that can help to signal which loan candidates have a higher or lower probability of paying their mortgage.